I'm just a product manager who knows only a little bit about writing codes, but this video made it really easy to understand the high level concept and get the hang of lang chain. Big shoutout from Japan🍣
Thank you for this really helpful tutorial! It has helped me discover many things to which I was previously unaware of. No more doing things in an amateur way haha!😄
this is awesome. as someone who fails with some silly error everytime they try coding, this is the first time i've been able to fluently follow through a tutorial without hiccups. big kudos to you and great work with your explanations. excited to work through your series
Yesterday I finally had a breakthrough and am beginning to understand the things that I see and read. I just hope that I don't have to use API keys as I want EVERYTHING local until I want to access the 'net for more information. I am building a fairly comprehensive application that not only will order groceries but will also perform local actions. What a time to be alive.
You Good sir are not a Guy who talks the talk. I learnt more about Langchain from you in this half hour than anybody else I have listened to on the last 3months. The veritable quarter to be exact. You are a Guy who walks the walk 🫡
Thanks again, Greg! This video on LangChain concepts was really helpful after watching your LangChain intro. Learning about schemas, models, prompts, etc. is giving me a much better understanding of how LangChain works. Onward to the next video in your playlist!
I've watched 4 of your videos now, and the "set" and video quality have incrementally improved. I appreciate you putting in the effort to make your videos better. I look forward to watching and learning from your future videos!
Very nice intro, thank you Greg. A good starting point to dig in deeper. Now looking forward to the second part with some use cases and then stop watching videos and get the hands on it. But rest assured, I will sure come back for more videos later. Love your work, please keep it going. Greetings and be well, sir.
Took me a while to realize the parsing is done by the llm and all you're doing is giving it instructions on how to parse. In hindsight, it's obvious that's what would be done but I'm still amazed and surprised all at once.
Amazing job explaining the core concepts, this video + the cook book are THE fast references to understand more and memorize less and practice and develop even more. Thanks a million sir
It has become very difficult to keep up with the ML/DL/AI scene as of lately, so I decided to go with Lang ⛓️, and your video has been the best I've seen so far. Thank you for your effort.
I will write the comment on this video but thanks too much for ALL the videos, code and your explanations. Keep going please, you have talent for this! waiting for new lessons sir!
@@DataIndependent Hi Greg, I'm a web developer. Recently I tried openai's whisper to do subtitles and I'm amazed by its accuracy. I've also been curious about what Langchain is and how it can used. you offered a great explanation. 🙏
This is really helpful. With the order that those concepts are introduced with the great examples, I found everything in the langchain documentation become much easier to follow now. I now know what to look at for each of the ideas I have. Thank you!
I guess we can run it through your cookbook too right? If yes, how would integrating it into my website work? Can we also copy it's code exactly for our initial templates?
Thank you so much for making this so easy to follow and understand. As someone who has been out of the coding game for 15 years, I really struggled with some of the content from others where the assumed knowledge and terminology is so much higher. Keep up the good work :)
@@DataIndependent An app that helps users draft a specific type form of words. I'd like to use an agent that will follow a general process to gather information, then evaluate whether it has enough to draft the text against specific criteria, and ask for more if not. Once it thinks it has enough, it will draft the form of words. Evaluation seems tricky though!
Excellent instruction! You've made what could be a complex topic, very simple. Hope you can do a video on embedding and the various use cases. Thank you for the excellent presentation in this video.
Good review of the framework. in 12:31 you mentioned the use of triple quotes for fanciness. However, I think they work well for multiline strings. just my thought. Keep it up though, I liked this alot
Excellent, clear video, inspired me to check out more of your content - cheers! On an aside, anyone ever mentioned that you kinda look like Dennis from Always Sunny? 😅
Beautiful summary! Thanks a lot for sharing it. I'll definitely check out all the documentation but you gave us a very good overview. Thanks for the ramp up!
Thank you for this amazingly helpful overview! Lucky to have this as my intro to GPT world. I have a question regarding splitters and embeddings. I'm working on an application that stores chat history of coaches with their clients and allows quickly find the references from the previous conversations with the user. Let's say he mentioned his dog, so instead of scrolling the chart and trying to find his dog's name and type, I can simply ask GPT and get the name. Would you rather save each message as a different doc/embedding or the whole conversation as one doc?
Thanks for great overview. Even as a dev myself I find the docs are dooing a poor job of explaining what is for what and why. You did incredible job at this. Thanks!
Hi Greg, thanks for the video series. A topic that I would like covered is how to do unittesting of components that interact with a LLM to produce its result. Thank you
Nice one, to the point. One clarification.. we have some sensitive data which should not be sent externally In this case such as langchain.vectorstores stores locally, what sort of information goes externally to openAI or outside company network
Thanks a lot for making this! I love that you just went through the notebook, giving us clear and concise overviews of each step.
Wow this is so cool! Love the tip, I hardly get them.
Thank you!
As usual, very lucid and high quality content. I think I should embed the youtube transcripts and prompt gpt to 'explain it like data independent'. 😂
Nice! That's fun thank you
Literally amazed at how easily you went through such complex concepts.
Nice and inspiring examples, good job!
This is super high-quality content. Well done man!
Glad you enjoy it!
I can't appreciate this video or this playlist more. This work is a masterpiece. Thank you!!
Thank you, I learned so much reading your Cookbook.
Oh heck ya! This is my 2nd tip ever. Love it.
Reach out if you have any questions
I'm just a product manager who knows only a little bit about writing codes, but this video made it really easy to understand the high level concept and get the hang of lang chain.
Big shoutout from Japan🍣
Thank you for this really helpful tutorial! It has helped me discover many things to which I was previously unaware of. No more doing things in an amateur way haha!😄
Nice! This notebook needs updating forsure
this is awesome. as someone who fails with some silly error everytime they try coding, this is the first time i've been able to fluently follow through a tutorial without hiccups. big kudos to you and great work with your explanations. excited to work through your series
You used the colab notebook to follow the code?
Where has this channel been all this while? This is gold. Thanks for the great video!
Yesterday I finally had a breakthrough and am beginning to understand the things that I see and read. I just hope that I don't have to use API keys as I want EVERYTHING local until I want to access the 'net for more information. I am building a fairly comprehensive application that not only will order groceries but will also perform local actions. What a time to be alive.
You Good sir are not a Guy who talks the talk. I learnt more about Langchain from you in this half hour than anybody else I have listened to on the last 3months. The veritable quarter to be exact. You are a Guy who walks the walk 🫡
Thanks again, Greg! This video on LangChain concepts was really helpful after watching your LangChain intro. Learning about schemas, models, prompts, etc. is giving me a much better understanding of how LangChain works. Onward to the next video in your playlist!
I've watched 4 of your videos now, and the "set" and video quality have incrementally improved. I appreciate you putting in the effort to make your videos better. I look forward to watching and learning from your future videos!
Best langchain explanation I have seen so far. Fast paced. Brilliant.
I am amazed at how well you explained these concepts 🤯Keen to read your newsletters!
Love it! Thank you!
I’m amazed how dense and well indexed this video and document is
Nice! Thank you
What is abundantly evident is that you, @DataIndependent, are an excellent teacher🙏.
nice! thank you Krbabu that's nice
High level/big picture explanations like this are very useful to some of us. Thank you
Nice! Glad it worked out
In just a few minutes, I became a really big fan! Thank you for your videos!
Nice! Thank you Gabriel
This should be a college lecture for all CS students since 2023.
Wow that is an awesome compliment thank you
Okay beta
there won't be a need for a CS degree by 2025...
even in the data science field...
Huh? What's college?
@@greendsnowvery true I didn’t get a degree and I’m working in the CS field. Not easy though
Very nice intro, thank you Greg. A good starting point to dig in deeper. Now looking forward to the second part with some use cases and then stop watching videos and get the hands on it. But rest assured, I will sure come back for more videos later. Love your work, please keep it going. Greetings and be well, sir.
I love the support! Thank you Markus
Finally found the clear and intuitive lecture on how to smart use of LLMs by langchain and other search tools. Thank you so much.
Nice! Thank you
I had zero knowledge about it and was struggle to understand it. now I have fairly good idea that Langchain is and what it can do with. thanks a lot.
One of the best and concise summary on the core concepts of LangChain. I highly recommend it. Thank you.
Wow. The power and possibilities are endless! I hooked already.
I have started using Langchain. The video is what I need. Thank you.
Took me a while to realize the parsing is done by the llm and all you're doing is giving it instructions on how to parse. In hindsight, it's obvious that's what would be done but I'm still amazed and surprised all at once.
Awesome explanation. So clear! I loved that you just went step by step through the notebook.
Your way of explaining is just flawless. Really helpful material, provided in a perfect manner. Congrats!
Nice! Thank you and glad to hear it
Fantastic video. I learned a ton in 60 minutes, by watching this video
Looking forward to watch the rest as well
Nice! Glad to hear it Prasanna!
Greg, thanks for so generously sharing your knowledge! I like the new navy paint on the walls in your room. 👍🏻
Thank you! it was time for an upgrade
Best video I followed all way long. Thanks Greg. This is Quality content!
Glad you enjoyed it! What're you building
This is indeed a Cookbook, very good job, eagerly waiting for the use cases video, thank you!
Glad you liked it!
Great, correct, incisive, ultimate pragmatic video explanation, completely zero-based social science students eager to listen
Nice! Thanks
Too relaxing to learn with you!! The way you communicate is very nice and clear, thank you
Thanks for the kind comments!
Amazing job explaining the core concepts, this video + the cook book are THE fast references to understand more and memorize less and practice and develop even more. Thanks a million sir
With this attitude your channel will be a start in the upcoming months/years.Keep up the great work..
Nice thank you!
It has become very difficult to keep up with the ML/DL/AI scene as of lately, so I decided to go with Lang ⛓️, and your video has been the best I've seen so far. Thank you for your effort.
I will write the comment on this video but thanks too much for ALL the videos, code and your explanations. Keep going please, you have talent for this! waiting for new lessons sir!
Awesome, thanks you Rocio
Thank you - I am a development editor, and I built a little tool to help ask questions of the first draft text I am sent from what I learnt from you.
Nice!
Hello Rob. Do you have a demo reel of your project?
The best explanation I have found on UA-cam , thank you!
Awesome thanks Hoyin - what're you working on?
@@DataIndependent Hi Greg, I'm a web developer. Recently I tried openai's whisper to do subtitles and I'm amazed by its accuracy.
I've also been curious about what Langchain is and how it can used. you offered a great explanation. 🙏
Thanks a lot Greg Kamradt for this video, It made me understand very clearly LangChain's coponents.
You aced the topic man!. Thanks.
That was a brilliant video. So well described with logical, easily understood examples. Thank you!
Glad it was helpful!
Greg, thanks for another great video. I've come back to this one a few times to clear my head :)
Useful contributions. Thanks your helping the community, Bro!
Nice! Thanks Tim
Great overview Greg! Really enjoyed the examples and the way you broke down the concepts.
Nice!! Thanks man
This is really helpful. With the order that those concepts are introduced with the great examples, I found everything in the langchain documentation become much easier to follow now. I now know what to look at for each of the ideas I have. Thank you!
Nice! glad to hear it.
Dude finding this video was one of the best things that happened to me in life
I guess we can run it through your cookbook too right? If yes, how would integrating it into my website work? Can we also copy it's code exactly for our initial templates?
Well crafted overview with concrete examples. I'm very experienced in the field, and this taught me quite a bit.
Great thank you George.
What’re you working on or building?
Great coverage and explanation of Langchain Greg. Thanks for this!
Awesome thank you! What’re you building?
Kudos to you reffort on doing this. Very helpful. Thank you
Brilliant! Would love to see you do one on building a personal assistent with LangChain!
Spectacular video. Thank you.
Glad you enjoyed it!
Loving the new look bro! Great upgrade and as usual great conent
Nice! Thank you very much. It was time to take AI more seriously.
I'm about to rebrand data indy to my personal brand as well.
All of a sudden, I liked this course. Great content.
Awesome introduction about LangChain, great job!
thanks greg, this was very very easy to understand and insightful
amazing playlist...watching it completely for sure
Thank you for this video! You did an amazing job, learning from which we will also do amazing jobs!
BRAVO! Clear, concise, and to the point. Thank you.
What an amazing video to walk you through the concepts, as well as practical examples. I recommended my friend to watch it too. 😊
Thank you! I’m going to be doing an update soon. Too much code is out of date.
Very impressive communication skills!
Amazing and great explanation, Ill try out the cookbook in Git. Thank you
Thank you so much for making this so easy to follow and understand. As someone who has been out of the coding game for 15 years, I really struggled with some of the content from others where the assumed knowledge and terminology is so much higher. Keep up the good work :)
Awesome! Thank you very much - what projects are you working on building?
@@DataIndependent An app that helps users draft a specific type form of words. I'd like to use an agent that will follow a general process to gather information, then evaluate whether it has enough to draft the text against specific criteria, and ask for more if not. Once it thinks it has enough, it will draft the form of words. Evaluation seems tricky though!
U just blew my mind!!!, jumping into your langchaing guided tour to figure out ways to tame OpenAI 💥
Nice! Thank you
Excellent instruction! You've made what could be a complex topic, very simple. Hope you can do a video on embedding and the various use cases. Thank you for the excellent presentation in this video.
Awesome thank you!
For embeddings, what is the real world use case you want to explore more?
Good review of the framework. in 12:31 you mentioned the use of triple quotes for fanciness. However, I think they work well for multiline strings. just my thought. Keep it up though, I liked this alot
Nice! Thank you for that.
Thank you for your work Greg! Regards from Belgium :)
Insanely high quality video. Thanks so much!
Glad you enjoyed it!
This is awesome !!! Please keep up ! All my support
awesome video. the concepts are explained clearly!
Love it thank you Vers.
I am gonna set this up to ask questions about langchain to keep me updated with langchain :D
Just Awesome .. Thanks a lot for making and sharing this video ..
This is a great presentation. You have a great way of teaching.
Good stuff. Even as a developer the concepts of AI are some completely new so thanks for breaking the concepts down into simple language
Fantastic tutorial. One of the best I found. Great job! Subscribed
Nice! Thank you
Fantastic presentation! This is incredibly useful. Thank you!
Awesome! Thank you
Yes! Only tutorial that makes any sense. Great job thank you!!
Awesome! Thanks Mel!
The best overview ever!!
Awesome, thank you!
This video was a really great beginner overview. Thanks a lot for putting it together. I'm looking forward to part 2.
He got a whole playlist ( 16 episodes ), this one is the 3rd one, you can check it out if you haven't
Excellent, clear video, inspired me to check out more of your content - cheers!
On an aside, anyone ever mentioned that you kinda look like Dennis from Always Sunny? 😅
Dude. Epic💪🏾💪🏾💪🏾💪🏾💪🏾
👏🏾thanks for this Masterclass!
Big thanks for publishing such great content.
Thank you very much! This is super helpful for a Langchain Beginner LOL. Looking forward to your use cases!
Thanks Heqing - Working on it
Beautiful summary! Thanks a lot for sharing it. I'll definitely check out all the documentation but you gave us a very good overview. Thanks for the ramp up!
Nice glad to hear it
Thank you for this concise and understandable introduction of the concepts!
Glad it was helpful!
Thank you for the great Cookbook!
Nice! Hope it's fun
Thank you for this amazingly helpful overview! Lucky to have this as my intro to GPT world.
I have a question regarding splitters and embeddings. I'm working on an application that stores chat history of coaches with their clients and allows quickly find the references from the previous conversations with the user. Let's say he mentioned his dog, so instead of scrolling the chart and trying to find his dog's name and type, I can simply ask GPT and get the name. Would you rather save each message as a different doc/embedding or the whole conversation as one doc?
This is a really concise & cool tutorial to start with langchain! Thank you.
Glad it was helpful!
Thank you so much for the video. It was really very helpful. You explained the concepts very well. 🙏
You are a great teacher!
Thanks for great overview. Even as a dev myself I find the docs are dooing a poor job of explaining what is for what and why. You did incredible job at this. Thanks!
Thank you for the guide cookbook! 谢谢你精彩的cookbook！
Awesome! Glad it worked
Super interesting and thorough - thanks!
Nice! Thank you
Excellent tutorial, thanks for sharing
highly appreciate your work 💖
Awesome thank you
Hi Greg, thanks for the video series. A topic that I would like covered is how to do unittesting of components that interact with a LLM to produce its result. Thank you
Nice thanks Jakob - I'll add that to the list
Nice one, to the point. One clarification.. we have some sensitive data which should not be sent externally In this case such as langchain.vectorstores stores locally, what sort of information goes externally to openAI or outside company network